System Requirements:
Windows 11 24H2
Python (code developed using 3.12.4)

Installation:
https://www.python.org/downloads/

To install the required packages, open command prompt and use the following commands:
pip install pandas
pip install matplotlib
pip install scikit-learn
pip install scipy

Keep all Python code in the same folder.

Install time may vary based on internet connection speed.

Instructions:
Demo Data Included = Demo_Raw_Data.csv
1.) Create folders called "input_folder" and "output_folder" in the same path with the Python code.
2.) Update the "input_folder", "output_folder", and "udf_path" variables in signal_check_wrap.py to the same path with the Python code and save.
3.) Organize a .csv input file as follows:
	Row 1 = column titles (Time (s), 465 nm Channel, 405 nm Channel)
	Column 1 = time stamps for photometry recording.
	Column 2 = 465 nm signal (GCaMP Channel).
	Column 3 = 405 nm signal (Control Channel).
4.) Place .csv input files into the input_folder.
5.) Double-click signal_check_wrap.py or type signal_check_wrap.py into command prompt and press enter to run.

Output:
The output_folder will contain a .csv file with timestamps, 465 nm channel, 405 nm channel, 405 nm fitted channel, and DF/F0. There will be plots of the 465 nm and fitted 405 nm channels and the DF/F0 trace. Run time is ~1.5 minutes depending on recording length and sampling rate.